Prognostic value of tumor deposits in rectal cancer: A monocentric series of 505 patients

The past, present, and future of tumour deposits in colorectal cancer: Advancing staging for improved prognosis and treatment decision-making

Tumour deposits (TDs) significantly impact colorectal cancer (CRC) prognosis. Integrating TDs into the TNM staging system can enhance individualized disease management. Keeping abreast of evolving TDs research is pivotal for clinical advancement. We comprehensively reviewed both recent and popular literature to grasp the field's essence. Subsequently, a data retrieval sourced articles on TDs in CRC for bibliometric analysis, spanning from 1 January 1935 to 30 April 2023. Bibliometrix software facilitated paper analysis and visualization. Bibliometric indicators, the trends and hotspots were determined. A total of 2147 articles were successfully retrieved. Brown G emerged as the most productive author, and the USA as the most prolific country. Central South University and Memorial Sloan Kettering Cancer Center led productivity. Bradford's law categorized 48 journals into zone 1. Keywords co-occurrence analysis identified three main clusters: the application of TDs in TNM staging, the pathogenesis of TDs, and the assessment of TDs. The trend topic analysis highlighted research focused on refining TDs incorporation into tumour staging. TDs wield enduring medical significance, shaping ongoing research. Much literature focused on confirming TD's prognostic value and optimizing TNM integration. Additionally, it is worth highlighting that TD's enigmatic pathogenesis demands research priority, as it holds the potential to unveil concealed knowledge regarding their development.

Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer

OBJECTIVE

To investigate the value of radiomics analysis of dual-layer spectral-detector computed tomography (DLSCT)-derived iodine maps for predicting tumor deposits (TDs) preoperatively in patients with colorectal cancer (CRC).

MATERIALS AND METHODS

A total of 264 pathologically confirmed CRC patients (TDs + (n = 80); TDs - (n = 184)) who underwent preoperative DLSCT from two hospitals were retrospectively enrolled, and divided into training (n = 124), testing (n = 54), and external validation cohort (n = 86). Conventional CT features and iodine concentration (IC) were analyzed and measured. Radiomics features were derived from venous phase iodine maps from DLSCT. The least absolute shrinkage and selection operator (LASSO) was performed for feature selection. Finally, a support vector machine (SVM) algorithm was employed to develop clinical, radiomics, and combined models based on the most valuable clinical parameters and radiomics features. Area under receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis were used to evaluate the model's efficacy.

RESULTS

The combined model incorporating the valuable clinical parameters and radiomics features demonstrated excellent performance in predicting TDs in CRC (AUCs of 0.926, 0.881, and 0.887 in the training, testing, and external validation cohorts, respectively), which outperformed the clinical model in the training cohort and external validation cohorts (AUC: 0.839 and 0.695; p: 0.003 and 0.014) and the radiomics model in two cohorts (AUC: 0.922 and 0.792; p: 0.014 and 0.035).

CONCLUSION

Radiomics analysis of DLSCT-derived iodine maps showed excellent predictive efficiency for preoperatively diagnosing TDs in CRC, and could guide clinicians in making individualized treatment strategies.

CLINICAL RELEVANCE STATEMENT

The radiomics model based on DLSCT iodine maps has the potential to aid in the accurate preoperative prediction of TDs in CRC patients, offering valuable guidance for clinical decision-making.

KEY POINTS

Accurately predicting TDs in CRC patients preoperatively based on conventional CT features poses a challenge. The Radiomics model based on DLSCT iodine maps outperformed conventional CT in predicting TDs. The model combing DLSCT iodine maps radiomics features and conventional CT features performed excellently in predicting TDs.

Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer

BACKGROUND

The use of peritumoral features to determine the survival time of patients with rectal cancer (RC) is still imprecise.

PURPOSE

To explore the correlation between intratumoral, peritumoral and combined features, and overall survival (OS).

STUDY TYPE

Retrospective.

POPULATION

One hundred sixty-six RC patients (53 women, 113 men; average age: 55 ± 12 years) who underwent radical resection after neoadjuvant therapy.

FIELD STRENGTH/SEQUENCE

3 T; T2WI sagittal, T1WI axial, T2WI axial with fat suppression, and high-resolution T2WI axial sequences, enhanced T1WI axial and sagittal sequences with fat suppression.

ASSESSMENT

Radiologist A segmented 166 patients, and radiologist B randomly segmented 30 patients. Intratumoral and peritumoral features were extracted, and features with good stability (ICC ≥0.75) were retained through intra-observer analysis. Seven classifiers, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), Extremely randomized trees (ET), eXtreme Gradient Boosting (XGBoost), and LightGBM (LGBM), were applied to select the classifier with the best performance. Next, the Rad-score of best classifier and the clinical features were selected to establish the models, thus, nomogram was built to identify the association with 1-, 3-, and 5-year OS.

STATISTICAL TESTS

LASSO, regression analysis, ROC, DeLong method, Kaplan-Meier curve. P < 0.05 indicated a significant difference.

RESULTS

Only Node (irregular tumor nodules in the surrounding mesentery) and ExtraMRF (lymph nodes outside the perirectal mesentery) were significantly different in 20 clinical features. Twelve intratumoral, 3 peritumoral, and 14 combined features related to OS were selected. LR, SVM, and RF classier showed the best efficacy in the intratumoral, peritumoral, and combined model, respectively. The combined model (AUC = 0.954 and 0.821) had better survival association than the intratumoral model (AUC = 0.833 and 0.813) and the peritumoral model (AUC = 0.824 and 0.687).

DATA CONCLUSION

The proposed peritumoral model with radiomics features may serve as a tool to improve estimated survival time.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 4.

MRI-based multiregional radiomics for preoperative prediction of tumor deposit and prognosis in resectable rectal cancer: a bicenter study

OBJECTIVE

To build T2WI-based multiregional radiomics for predicting tumor deposit (TD) and prognosis in patients with resectable rectal cancer.

MATERIALS AND METHODS

A total of 208 patients with pathologically confirmed rectal cancer from two hospitals were prospectively enrolled. Intra- and peritumoral features were extracted separately from T2WI images and the least absolute shrinkage and selection operator was used to screen the most valuable radiomics features. Clinical-radiomics nomogram was developed by radiomics signatures and the most predictive clinical parameters. Prognostic model for 3-year recurrence-free survival (RFS) was constructed using univariate and multivariate Cox analysis.

RESULTS

For TD, the area under the receiver operating characteristic curve (AUC) for intratumoral radiomics model was 0.956, 0.823, and 0.860 in the training cohort, test cohort, and external validation cohort, respectively. AUC for the peritumoral radiomics model was 0.929, 0.906, and 0.773 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for combined intra- and peritumoral radiomics model was 0.976, 0.918, and 0.874 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for clinical-radiomics nomogram was 0.989, 0.777, and 0.870 in the training cohort, test cohort, and external validation cohort, respectively. The prognostic model constructed by combining intra- and peritumoral radiomics signature score (radscore)-based TD and MRI-reported lymph nodes metastasis (LNM) indicated good performance for predicting 3-year RFS, with AUC of 0.824, 0.865, and 0.738 in the training cohort, test cohort and external validation cohort, respectively.

CONCLUSION

Combined intra- and peritumoral radiomics model showed good performance for predicting TD. Combining intra- and peritumoral radscore-based TD and MRI-reported LNM indicated the recurrence risk.

CLINICAL RELEVANCE STATEMENT

Combined intra- and peritumoral radiomics model could help accurately predict tumor deposits. Combining this predictive model-based tumor deposits with MRI-reported lymph node metastasis was associated with relapse risk of rectal cancer after surgery.

KEY POINTS

• Combined intra- and peritumoral radiomics model provided better diagnostic performance than that of intratumoral and peritumoral radiomics model alone for predicting TD in rectal cancer. • The predictive performance of the clinical-radiomics nomogram was not improved compared with the combined intra- and peritumoral radiomics model for predicting TD. • The prognostic model constructed by combining intra- and peritumoral radscore-based TD and MRI-reported LNM showed good performance for assessing 3-year RFS.

A nomogram for preoperative differentiation of tumor deposits from lymph node metastasis in rectal cancer: A retrospective study

The objective is to develop and validate a combined model for noninvasive preoperative differentiating tumor deposits (TDs) from lymph node metastasis (LNM) in patients with rectal cancer (RC). A total of 204 patients were enrolled and randomly divided into 2 sets (training and validation set) at a ratio of 8:2. Radiomics features of tumor and peritumor fat were extracted by using Pyradiomics software from the axial T2-weighted imaging of MRI. Rad-score based on extracted Radiomics features were calculated by combination of feature selection and the machine learning method. Factors (Rad-score, laboratory test factor, clinical factor, traditional characters of tumor on MRI) with statistical significance were integrated to build a combined model. The combined model was visualized by a nomogram, and its distinguish ability, diagnostic accuracy, and clinical utility were evaluated by the receiver operating characteristic curve (ROC) analysis, calibration curve, and clinical decision curve, respectively. Carbohydrate antigen (CA) 19-9, MRI reported node stage (MRI-N stage), tumor volume (cm3), and Rad-score were all included in the combined model (odds ratio = 3.881 for Rad-score, 2.859 for CA19-9, 0.411 for MRI-N stage, and 1.055 for tumor volume). The distinguish ability of the combined model in the training and validation cohorts was area under the summary receiver operating characteristic curve (AUC) = 0.863, 95% confidence interval (CI): 0.8-0.911 and 0.815, 95% CI: 0.663-0.919, respectively. And the combined model outperformed the clinical model in both training and validation cohorts (AUC = 0.863 vs 0.749, 0.815 vs 0.627, P = .0022, .0302), outperformed the Rad-score model only in training cohorts (AUC = 0.863 vs 0.819, P = .0283). The combined model had highest net benefit and showed good diagnostic accuracy. The combined model incorporating Rad-score and clinical factors could provide a preoperative differentiation of TD from LNM and guide clinicians in making individualized treatment strategy for patients with RC.

Negative Prognostic Impact of Tumor Deposits in Rectal Cancer: A National Study Cohort

OBJECTIVE

To investigate whether tumor deposits (TDs) in rectal cancer are associated with increased recurrence risk and decreased survival.

BACKGROUND

Tumor deposits (TDs) are considered a risk factor for recurrence after colon cancer resection, and the presence of TDs prompts adjuvant chemotherapy. The prognostic relevance of TDs in rectal cancer requires further exploration.

METHODS

All patients treated with abdominal resection surgery for rectal cancer in Sweden between 2011 and 2014 were eligible for inclusion in this retrospective cohort study based on prospectively collected data from the Swedish Colorectal Cancer Registry. The primary endpoint was local recurrence or distant metastasis. Secondary outcomes were overall and relative survival.

RESULTS

Five thousand four hundred fifty-five patients were identified of which 3769 patients were analyzed after exclusion. TDs were found in 404 (10.7%) patients, including 140 (3.7%) patients with N1c-status. In TD-positive patients, local recurrence and distant metastasis rates at 5 years were 6.3% [95% CI 3.8-8.8%] and 38.9% [95% CI, 33.6-43.5%] compared with 2.7% [95% CI, 2.1-3.3%] and 14.3% [95% CI, 13.1-15.5%] in TD-negative patients. In multivariable regression analysis, the risk of local recurrence and distant metastasis were increased; HR 1.86 [95% CI, 1.09-3.19; P =0.024] and 1.87 [95% CI, 1.52-2.31; P =<0.001], respectively. Overall survival at 5 years was 68.8% [95% CI, 64.4-73.4%] in TD-positive patients and 80.7% [95% CI, 79.4-82.1%] in TD-negative patients. pN1c-patients had similar outcomes regarding local recurrence, distant metastasis, and survival as pN1a-b stage patients. TD-positive pN1a-b patients had significantly worse outcomes whereas TDs did not affect outcomes in pN2a-b patients.

CONCLUSION

This study suggests that TDs have a negative impact on the prognosis in rectal cancer. Thus, efforts should be made to diagnose TD-positive rectal cancer patients preoperatively.

Adverse impact of tumor deposits in lymph node negative rectal cancer - a national cohort study

PURPOSE

This study aimed to investigate the prognostic effect of tumor deposits (TDs) in lymph node negative rectal cancer.

METHODS

Patients who had undergone surgery for rectal cancer with curative intention between 2011 and 2014 were extracted from the Swedish Colorectal Cancer Registry. Patients with positive lymph nodes, undisclosed TD status, stage IV disease, non-radical resections, or any outcome (local recurrence (LR), distant metastasis (DM) or mortality) within 90 days after surgery were excluded. TDs status was based on histopathological reports. Cox-regression analyses were used to examine the prognostic impact of TDs on LR, DM, and overall survival (OS) in lymph node-negative rectal cancer.

RESULTS

A total of 5455 patients were assessed for inclusion of which 2667 patients were analyzed, with TDs present in 158 patients. TD-positive patients had a lower 5-year DM-free survival (72.8%, p < 0.0001) and 5-year overall survival (75.9%, p = 0.016), but not 5-year LR-free survival (97.6%) compared to TD-negative patients (90.2%, 83.1% and 95.6%, respectively). In multivariable regression analysis, TDs increased the risk of DM [HR 4.06, 95% CI 2.72-6.06, p < 0.001] and reduced the OS [HR 1.83, 95% CI 1.35-2.48, p < 0.001]. For LR, only univariable regression analysis was performed which showed no increased risk of LR [HR 1.88, 95% CI 0.86-4.11, p = 0.11].

CONCLUSION

TDs are a negative predictor of DM and OS in lymph node-negative rectal cancer and could be taken into consideration when planning adjuvant treatment.

Oncological outcome after lateral pelvic lymphadenectomy for low rectal carcinoma: not only an N-status matter

Tumour deposits (TDs), novel pathological entities, should be considered when estimating the regional and systemic spread of rectal carcinoma and formulating treatment strategies. In fact, TDs may have more severe prognostic impact than lymph node positivity or the lymph node ratio. The assessment of the presence of TDs can be performed only through accurate postoperative pathological examination; however, the detection of TDs is not part of any of the procedures currently used to assess preoperative or intraoperative staging. This review aims to analyse and discuss the impact of TDs on the oncological outcome of patients who undergo surgery for advanced low rectal carcinoma. No prospective study has evaluated the impact of lateral pelvic TDs on oncological outcomes following total mesorectal excision with lateral pelvic lymphadenectomy. Although adequate total mesorectal excision allows for the excision of intramesorectal TDs, lateral pelvic lymph node dissection cannot guarantee the removal of lateral pelvic TDs; moreover, it remains to be determined whether surgical excision of lateral pelvic TDs can impact long-term outcomes. However, the identification of lateral pelvic TDs strengthens the 'staging effect' and limits the 'therapeutic effect' of lateral pelvic lymphadenectomy, supporting the rationale for the use of neoadjuvant chemoradiotherapy for rectal cancer. When evaluating the oncological outcomes after total mesorectal excision with lateral pelvic lymphadenectomy, the impact of lateral pelvic TDs should be considered.

Radiomics for differentiating tumor deposits from lymph node metastasis in rectal cancer

BACKGROUND

Tumor deposits (TDs) are not equivalent to lymph node (LN) metastasis (LNM) but have become independent adverse prognostic factors in patients with rectal cancer (RC). Although preoperatively differentiating TDs and LNMs is helpful in designing individualized treatment strategies and achieving improved prognoses, it is a challenging task.

AIM

To establish a computed tomography (CT)-based radiomics model for preoperatively differentiating TDs from LNM in patients with RC.

METHODS

This study retrospectively enrolled 219 patients with RC [TDs⁺LNM^- (n = 89); LNM⁺ TDs^- (n = 115); TDs⁺LNM⁺ (n = 15)] from a single center between September 2016 and September 2021. Single-positive patients (i.e., TDs⁺LNM^- and LNM⁺TDs^-) were classified into the training (n = 163) and validation (n = 41) sets. We extracted numerous features from the enhanced CT (region 1: The main tumor; region 2: The largest peritumoral nodule). After deleting redundant features, three feature selection methods and three machine learning methods were used to select the best-performing classifier as the radiomics model (Rad-score). After validating Rad-score, its performance was further evaluated in the field of diagnosing double-positive patients (i.e., TDs⁺LNM⁺) by outlining all peritumoral nodules with diameter (short-axis) > 3 mm.

RESULTS

Rad-score 1 (radiomics signature of the main tumor) had an area under the curve (AUC) of 0.768 on the training dataset and 0.700 on the validation dataset. Rad-score 2 (radiomics signature of the largest peritumoral nodule) had a higher AUC (training set: 0.940; validation set: 0.918) than Rad-score 1. Clinical factors, including age, gender, location of RC, tumor markers, and radiological features of the largest peritumoral nodule, were excluded by logistic regression. Thus, the combined model was comprised of Rad-scores of 1 and 2. Considering that the combined model had similar AUCs with Rad-score 2 (P = 0.134 in the training set and 0.594 in the validation set), Rad-score 2 was used as the final model. For the diagnosis of double-positive patients in the mixed group [TDs⁺LNM⁺ (n = 15); single-positive (n = 15)], Rad-score 2 demonstrated moderate performance (sensitivity, 73.3%; specificity, 66.6%; and accuracy, 70.0%).

CONCLUSION

Radiomics analysis based on the largest peritumoral nodule can be helpful in preoperatively differentiating between TDs and LNM.

Significance of tumor deposits combined with lymph node metastasis in stage III colorectal cancer patients: a retrospective multi-center cohort study from China

PURPOSE

The study aimed to explore the value of tumor deposits in stage III colorectal cancer (CRC) and verify whether patients with more tumor deposit numbers have higher risk of recurrence.

METHODS

The retrospective cohort analysis was performed at two cancer centers of China. Stage III CRC patients who underwent radical resection at the center between April 2008 and February 2019 were identified. The Univariate/Multivariate Cox regression, Kaplan-Meier analysis, and PSM were recurrence-free survival (RFS) used.

RESULTS

Total 1080 stage III CRC patients (634 [58.7%] men; median [IQR] age, 60 [50-68] years) who underwent radical surgical resection were identified for inclusion in this study. Patients with tumor deposits had a 12.8% lower 3-year RFS (n = 236 [69.9%]) than the patients without tumor deposits (n = 844 [82.7%]) (P ≤ 0.0001). The 3-year RFS of patients with stage N2 (n = 335 [61.2%]) was 18.6% lower (P ≤ 0.0001) than the original cohort of patients with stage N1 (n = 745 [79.8%]), but it was similar to the RFS of patients with 4 or more tumor deposits plus lymph node metastases (n = 58 [61.4%]) (P = 0.91). The RFS for patients with 4 or more tumor deposits plus number of lymph node metastases (n = 58 [61.4%]) was 15.8% lower than the cohort of patients with 1-3 tumor deposits + number of lymph node metastases (n = 687 [77.2%]) (P = 0.001). Multivariate analysis confirmed that patients with 4 or more tumor deposits + the number of lymph node metastases (hazard ratio [HR], 1.88; 95% CI, 1.24-2.87) were independently associated with a shorter RFS.

CONCLUSION

The number of tumor deposits is an indicator of poor postoperative prognosis. It is necessary to incorporate the number of tumor deposits combined with the number of lymph node metastases to stratify postoperative stratification of stage III CRC, which may provide a new theoretical basis for adjuvant therapy for patients with N1 stage CRC after surgery.

Comparative study of radiomics, tumor morphology, and clinicopathological factors in predicting overall survival of patients with rectal cancer before surgery

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Radiomics analysis of pretreatment MR images could predict overall survival (OS) in patients.

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Clinical, pathological and MRI imaging indexes were included and models were established. Tumor morphological model, clinicopathological model, radiomics model and comprehensive model were used to evaluate the prognosis of patients with rectal cancer. It can explore the influence of the above factors on the prognosis of rectal cancer from multi-level and multi-angle.

•

The proposed radiomics nomogram showed better prognostic performance than the clinicopathological and imaging model in risk stratification and can classify patients into high- and low-risk groups with significant differences in OS.

We compared the ability of a radiomics model, morphological imaging model, and clinicopathological risk model to predict 3-year overall survival (OS) in 206 patients with rectal cancer who underwent radical surgery and had magnetic resonance imaging, clinicopathological, and OS data available. The patients were randomized to a training cohort (n = 146) and a verification cohort (n = 60). Radiomics features were extracted from preoperative T2-weighted images, and a radiomics score model was constructed. Factors that were significant in the Cox multivariate analysis were used to construct the final morphological tumor model and clinicopathological model. A comprehensive model in the form of a line chart was established by combining the three models. Ten radiomics features significantly related to OS were selected to construct the radiomics feature model and calculate the radiomics score. In the morphological model, mesorectal extension depth and distance between the lower tumor margin and the anal margin were significant prognostic factors. N stage was the only significant clinicopathological factor. The comprehensive model combined with the above factors had the best prediction performance for OS. The C-index had a predictive performance of 0.872 (95% confidence interval [CI]: 0.832–0.912) in the training cohort and 0.944 (95% CI: 0.890–0.990) in the verification cohort, which was better than for any single model. The comprehensive model was divided into high-risk and low-risk groups. Kaplan-Meier curve analysis showed that all factors were significantly correlated with poor OS in the high-risk group. A comprehensive nomogram based on multi-model radiomics features can predict 3-year OS after rectal cancer surgery.

Association of tumor deposits with tumor-infiltrating lymphocytes and prognosis in gastric cancer

Background

To investigate the relationship between tumor deposits (TDs) with the clinicopathological characteristics tumor-infiltrating lymphocytes (TILs) and prognosis of gastric cancer. Further analysis was done on the relationship between the number and maximum diameter of TDs with the clinicopathological characteristics and prognosis of gastric cancer.

Methods

The pathological findings of 369 patients with gastric cancer were retrospectively analyzed to observe the expression of TDs and the levels of stromal TILs. The relationship between TDs, clinicopathological characteristics, and levels of stromal TILs was compared using the chi-square test. Kaplan-Meier was used for survival analysis, and the log-rank test was used to determine the relationship between TDs and disease-free survival, cancer-specific survival, and overall survival. The prognostic value of TDs was assessed using multivariate Cox proportional hazards regression analysis. For further analysis, the optimal cutoff values for the number and maximum diameter of TDs were selected based on the receiver operating characteristic (ROC) curve.

Results

TDs were significantly associated with sex, lymphovascular invasion, perineural invasion, pathological T,N stage, and clinical stage (all P < 0.05). TILs levels are lower in TDs(+) group and higher in TDs(−) group. Compared with TDs(−) groups, TDs(+) group had poor disease-free survival, cancer-specific survival, and overall survival. TDs are negatively correlated with TILs, and TILs levels are lower in TDs(+) group and higher in TDs(−) group (P < 0.05). The samples are divided into the number of TDs (< 4 and ≥ 4) and the maximum diameter of TDs (< 7 mm and ≥ 7 mm). The number of TDs was significantly associated with pathological N stage (P < 0.05). The maximum diameter of TDs was significantly correlated with Lauren classification (P < 0.05) .TDs ≥ 4 had lower DFS, CSS, and OS (P < 0.05). The maximum diameter of TDs was not statistically significant with prognosis (P > 0.05).

Conclusion

TDs are independent prognosis predictors of gastric cancer. In the tumor microenvironment, TDs and TILs interact with each other to regulate the development of gastric cancer, thus affecting gastric cancer prognosis of patients. The number of TDs ≥ 4 has a worse prognosis compared to the number of TDs < 4.

Prognostic value of tumor deposits for long-term oncologic outcomes in patients with stage III colorectal cancer: a systematic review and meta-analysis

PURPOSE

The presence of tumor deposits (TDs) in colorectal cancer is associated with a poor prognosis. In patients with the concomitant presence of both TDs and lymph nodes (LNs), there is no staging option except for the number of positive LNs alone. Therefore, to determine the prognostic value of TDs in patients with stage III colorectal cancer, meta-analyses of survival outcomes of patients with TDs were performed comparing different subgroups based on the lymph node status.

METHODS

PubMed, EMBASE, and the Cochrane Library were searched. Data were pooled, and overall effect size was calculated using random-effect models. Outcome measures were 5-year overall survival (OS) and 5-year disease-free survival (DFS).

RESULTS

We included in the analysis 18 nonrandomized studies and 1 prospective study that examined 90,455 patients. N1c patients (TD + LN-) had worse 5-year DFS than TDs-negative stage III patients (TD-LN +) with a RR of 1.30 (95% CI 1.06-1.61, I² = 47%). In subgroup analysis, N1c patients had worse 5-year DFS (RR = 1.60, 95% CI = 1.25-2.05, I² = 40%) compared with TDs-negative N1 patients (TD-N1) whereas N1c patients had better 5-year OS (RR = 0.72, 95% CI = 0.62-0.83, I² = 0%) and 5-year DFS (RR = 0.75, 95% CI = 0.57-0.99, I² = 0%) compared with TDs-negative N2 patients (TD-N2).

CONCLUSIONS

These results may suggest that current nodal staging for colorectal cancer needs modification. The presence of TDs may have more adverse oncologic outcomes than TDs-negative N1 patients. More studies are warranted to further verify these results.